A systematic review of structural equation modeling in augmented reality applications

Abstract

The purpose of this study is to present a comprehensive review of the use of structural equation modeling (SEM) in augmented reality (AR) studies in the context of the COVID-19 pandemic. IEEE Xplore Scopus, Wiley Online Library, Emerald Insight, and ScienceDirect are the main five data sources for data collection from Jan 2020 to May 2021. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach was used to conduct the analysis. At the final stage, 53 relevant publications were included for analysis. Variables such as the number of participants in the study, original or derived hypothesized model, latent variables, direct/indirect contact with users, country, limitation/suggestion, and keywords were extracted. The results showed that a variety of external factors were used to construct the SEM models rather than using the parsimonious ones. The reports showed a fair balance between the direct and indirect methods to contact participants. Despite the COVID-19 pandemic, few publications addressed the issue of data collection and evaluation methods, whereas video demonstrations of the augmented reality (AR) apps were utilized. The current work influences new AR researchers who are searching for a theory-based research model in their studies.

The Perceptions of Prospective Digital Transformation Adopters: An Extended Diffusion of Innovations Theory

“…Thus, PLS-SEM approach was selected in the study design. Of the many techniques available for PLS-SEM [41], [42], the authors utilized the Generalized Structured Component Analysis (GSCA) due to its flexibility to work with even small samples [43], [44]. GSCA has been applied in various domains [37], [38], [45].…”